Compressing images, documents and other structured data is an ongoing challenge in order to save memory and/or reduce bandwidth requirements for communicating data. Digital images, including digital videos in video conferencing systems, medical image volumes and streams of depth frames captured by depth cameras of augmented reality computing devices contain huge amounts of data and it is a challenge to store, transfer and decompress/decode this in practical manners. The same situation is found for other types of structured data such as speech signals, documents, emails, text messages, sensor data collected by mobile devices, and others.
Conventional image and document compression systems are available which operate by identifying redundant information in videos, images or documents and collapsing that redundancy into an encoded form such that the encoded, compressed images or documents may be decompressed when required without significant loss as compared with the original. However, these conventional compression systems produce compressed images or documents which, once in their compressed form are not suitable for tasks other than storage and transmission. Such conventional techniques compress the images or documents to a certain extent and there is an ongoing desire to improve the amount of compression which can be achieved, whilst still enabling decompression without significant loss from the original.
The embodiments described below are not limited to implementations which solve any or all of the disadvantages of known data compression systems.